01 / Too many surfaces
One task. Five tabs.
Today, one small job means jumping around. Your customer looks up a deal, checks an order, scans recent activity, opens a calendar, then comes back to the CRM.
Managed Code / Your product in AI chats
Your customers can use your product just by asking ChatGPT.
They already live in AI chats. Now they can get real work done in your product from there.
Your app in ChatGPTyour product · connected
Update the CRM and schedule the follow-up.
Agent working
crm.update_recordRunning…Done
calendar.create_eventWaiting for approval
Approval required
calendar.create_eventSchedule the follow-up?Thursday, 10:00
Approve actionsEdit
Before anything important happens, your customer sees a clear “Approve” step. Nothing runs behind their back.Done across your product.
- CRM updated
- Calendar booked
The CRM updates, the meeting gets booked, and your customer gets a plain receipt showing exactly what was done.
How a task changes01
The old way: one task, five tabs. The new way: one sentence.
02 / One request
One clear request.
Now they just ask. Your product decides which approved actions can do it.
“Update the CRM and schedule the follow-up.”
03 / Result
Done across your product.
It gets done inside your product. The chat shows a clear result. Your permissions, your rules, and your record of what happened stay in charge.
The full path02
From a plain-language request to a result your product owns.
- 01Your customer asks in ChatGPT.
- 02Your product offers only the actions you approved.
- 03The customer confirms the one that matters.
- 04Your product does the work and saves the record.
- 05The result comes back in the chat, ready to check.
The product layer03
01 / The shift
The chat is becoming part of your product.
ChatGPT can now run apps, and more customers expect to get things done by asking. So the real question is simple: which customer task should work in a chat first?
02 / The layer
Keep your product. Add an easier way in.
We build a separate layer that sits in front of your product. The AI chat talks to that layer, and the layer runs only the actions you approved. It never reaches into your code.
- The actions you approve, and nothing else.
- Sign-in, the look inside the chat, and testing, all handled.
- Fast, monitored, and released on your schedule.
03 / The AI chats
One build. Three chats, each with its own rules.
ChatGPT, Claude, and Gemini all work through conversation, but each has its own sign-in, look, approval step, and release process. We set up and check all three.
Library / Full collections04
See it in practice.
Three sets of pages: short workflow examples, real technical proof, and the thinking behind the build. Start wherever you like.
01 / Examples
Here are real workflows that end in a result a person can check. Each one starts small and grows from there.
Open the page02 / Cases
Open-source code you can read, a live product we built, and a private enterprise pattern. See how the work holds up before you commit.
Open the page03 / Insights
Clear product choices matter more than the number of AI hosts on your roadmap.
Open the pageWhere this comes from.
Straight from the official OpenAI and Model Context Protocol documentation.
OpenAI · Apps in ChatGPT
Primary product announcement for apps and the Apps SDK in ChatGPT.
OpenAI · Apps SDK
Official guide to MCP servers, tools, authentication, and UI for ChatGPT apps.
Model Context Protocol · tools specification
Protocol reference for named, discoverable tools and their input and output contracts.
AI / Second opinion05
Not sure where to start? Ask an AI.
Paste this question into ChatGPT, Claude, or Gemini. It walks you through finding the one task your customers would most want to finish by chatting, instead of clicking through your app.
“I run a software product. Help me identify one high-value workflow my customers could finish inside ChatGPT instead of switching between tabs. Ask me about the product, the user, the action, the data it needs, permissions, and the safest small first release.”
The prompt is copied as a backup. Some AI chats may ask you to paste it after sign-in.
FAQ06
Questions, answered.
Is this just an MCP server?
No. The server is one piece. We do the whole job: we pick the customer task, set who can do what, handle the quirks of each AI chat, make the actions run fast, add monitoring, test it, and ship it.
Do we have to rebuild our product?
Almost never. Our layer sits in front of what your product already does. We start with one small workflow and grow from what works.
Will it work in ChatGPT, Claude, and Gemini?
The same build can serve all three. Each one has its own sign-in, look, approval step, and publishing rules, so we set up and test each one separately.
How do you keep it safe?
Your product decides what is allowed, and we keep that in charge. Every action is spelled out, every input is checked, and the customer sees an approval step before anything happens. Our layer sits beside your product, not inside it.
Where does it run? Does it touch our code?
It runs as a separate service in front of your product. It never goes into your code, and you still own your data.
What does it cost, and how fast?
A first workflow starts at €3,200 and goes live in about 7 days.
Contact us07
Put your product where your customers already are
We build the connection that lets your customers use your product inside ChatGPT and Claude. You approve every action. First workflow live in about 7 days, from €3,200.